Abstract 4197: Combined contrast enhanced ultrasound and photoacoustic imaging reveals both functional flow patterns and dysfunctional vascular pooling in tumor models
Bibliographic record
Abstract
Abstract The tumor vasculature and its hypoxic microenvironment are constantly undergoing changes. These alterations are key attributes associated with aggressive cancer phenotypes, raising the need for non-invasive methods to track these changes. Similarly, in many cases, various cancer treatments also affect tumor vasculature, and preferably – should be monitored. Dynamic contrast-enhance ultrasound (DCEUS) and photoacoustic (PA) imaging are two promising candidates. DCEUS has the ability to measure functional tissue perfusion, whereas multispectral PA imaging can be used to evaluate tissue oxygenation related parameters. This study investigates the relationship between blood perfusion, oxygen saturation levels and hemoglobin concentration in two hind-limb tumor models, and evaluates the ability of these two modalities to image vascular structures and functions. Xenograft tumors were induced in SHO mice using either LS174T human colorectal cancer cells (n = 6), or PC3 human prostate cancer cells (n = 6). Tumors were grown to a depth of 4-6 mm before imaging was performed using a laser integrated high-frequency ultrasound system (Vevo®LAZR, VisualSonics Inc.). Contrast enhanced images were collected after a 50μL bolus injection of MicroMarker ultrasound contrast agents (VisualSonics Inc.) using non-linear contrast imaging. Perfusion parameters were quantified after applying wavelet denoising to the DCEUS clips. PA images were acquired using a 21MHz linear array transducer with fiber optical bundles integrated to each side, used to deliver light from a 680-970 nm tunable laser. Oxygen saturation levels and hemoglobin concentration were estimated from the PA measurements using spectral un-mixing. Tumor vascularity and hypoxia were confirmed with immunohistochemistry staining for CD31 and CA9. Reasonable correlations were found between corresponding pixels in the DCEUS perfusion maps and oxygen saturation maps (R = 0.63 and R = 0.5 for LS174T and PC3 respectively). In contrast, the correlation between blood perfusion and hemoglobin concentration was nil for LS174T tumors (R = -0.1), and low for PC3 tumors (R = 0.34). This discrepancy was explained by the presence of blood pools in LS174T tumors, observed in tumor histology. The presence of hemoglobin inside regions of hemorrhage together with the limited capability to separate hypoxic and necrotic regions, impeded the ability of PA imaging to detect blood vessels inside tumors. Compared to PA imaging, DECUS provides better detection of functional vasculature and enables the visualization of single blood vessels around the tumor core, without including blood pools. This study demonstrates that a multi-modality imaging scheme combining DCEUS and PA imaging can provide both distinctive and complementary information on tumor microenvironment in experimental animal studies. Citation Format: Melissa Yin, Avinoam Bar-Zion, Dan Adam, Stuart Foster. Combined contrast enhanced ultrasound and photoacoustic imaging reveals both functional flow patterns and dysfunctional vascular pooling in tumor models. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 4197.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".